Data Scientist

Aura helps customers monitor, manage, and protect against the risks associated with their identities and personal information in a digital world. With adaptive technology, a seasoned team, and a first-of-its-kind product suite, Aura enables customers to manage disparate cybersecurity needs with ease. Backed by premier investors, WndrCo, General Catalyst, Ten Eleven Ventures, Accel, Madrone Capital and Warburg Pincus. Aura's category-defining business is a holistic personal digital security platform that unites best-in-class privacy, identity, and security products.

Trusted by more than 2 million customers, Aura has a team of more than 500 people worldwide and revenues over $220 million. Most importantly, this trajectory continues to show momentum and is supported by strong organic growth in addition to strategic customer acquisition. Aura’s leadership team has seen similar success before, having grown a start-up to a valuation of over $3 billion prior to exit. With a clear vision, strong alignment, and strategic M&A execution, Aura has assembled a stellar team and built a unique culture with incredible employees. Join us for the ride!

Reporting to the head of data science, we are seeking a creative and motivated Data Scientist to develop and deploy models as a part of our digital security products.  We have multiple large scale supervised and unsupervised ML projects that we intend to deploy in commercial software.  The ideal candidate will be able to understand our data sources and collaborate with domain experts to develop and deploy models as part of commercial offerings.  We are not necessarily seeking the candidate who can tune a model to have the best fit statistics, but someone willing and able to own the entire process of transforming raw data into a commercially viable deployed model.

• Develop and deploy ML models into commercial applications

• Create reproducible data processes to transform raw petabyte sized data sources into feature sets for modeling

• Transform abstract requirement into technical specifications for model development

• Develop and deploy business logic mixed with ML models that provide predictions to front end applications

• Design and implement processes for validating deployed models

• Troubleshoot deployed models

Qualifications:

• Degree in a quantitative field such as mathematics, computer science, physics, economics, engineering, statistics, operations research, quantitative social science, etc.).

• 5-10+ working experience in software/analytics environment

• 2+ years working in an environment where ML models are deployed at commercial scale

• Experience with unsupervised models or NLP is a plus

• Familiarity with programming for data science; ideally Python, SQL & Pyspark

• Familiarity with workflow orchestration tools such as Airflow, Luigi, or Prefect is desired

• Basic knowledge on software development principles and architecture.

• Ability to break down and understand complex business problems, define a solution and implement it using advanced quantitative methods.

• Solid oral and written communication skills, especially around analytical concepts and methods.

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